The Project by the Numbers
Questions Explored
How can AI support the design of visual course syllabi that are engaging, accessible, inclusive, and learner-centred, and what tools and workflows are most effective for this process?
- What limitations of traditional course syllabi can be addressed through AI-supported design?
- How can AI support the creation of visual, engaging, accessible, and learner-centered syllabi through effective tools and workflows?
- What pedagogical, accessibility, and practical considerations should guide the integration of AI into syllabus design?
Learning Outcomes Self-Evaluation
Personal Learning Goals Self-Evaluation
Key Takeaways
1. From a Static Document to a Learning Tool
This project offered me an opportunity to reflect, reorient, and rediscover the meaning and purpose of the course syllabus in teaching and learning. Rather than viewing the syllabus as a mundane, static, and primarily administrative document, I began to see its potential as a visually engaging and interactive learning tool. Several studies have argued for the untapped potential of the traditional syllabus, proposing approaches such as the inclusive syllabus, learner-focused syllabus, liquid syllabus, and visual syllabus. However, implementing these alternative approaches can be challenging in practice, particularly given the time, technology, and design expertise required of instructors. During this project, I realized that AI has the potential to lower some of these barriers by making the process of visualizing and transforming course content more accessible and efficient. Exploring these possibilities—and thinking critically about how AI can be used most effectively—was an eye-opening, hands-on learning experience for me, both as a learning designer and as a student.
2. Start with Intention, Not Tools
One of my biggest takeaways from this project is that the focus should be on intention, not the tools. AI is simply one of many tools that can help bring an idea to life; it should not become the end goal. The more important questions are not whether to use AI, but why to use it and how it can support instructional goals.
Before creating a visual syllabus, I would start by asking: Why do I want to make this syllabus more visual? Is it simply because a visual format looks more appealing, or is there a specific purpose related to student learning, navigation, accessibility, or engagement? Which sections would benefit most from being presented in a visual or interactive format? And, most importantly, why would this change be meaningful for my students and me?
Having a clear purpose and intention, rather than focusing primarily on the available tools, can guide design decisions and lead to a visual syllabus that genuinely meets instructional needs and supports student learning.
3. Start Small and Iterate
I would also recommend not trying to visualize an entire syllabus at once, especially on a first attempt. AI may take the design in a direction different from what you initially envisioned, generating text, images, or layouts that do not necessarily align with your course goals or instructional needs.
Instead, I found a segmented and iterative approach more useful. Start by critically reviewing the syllabus and identifying one or two sections that would benefit most from visual enhancement. Then, experiment with different AI tools and iterate on the designs. Comparing multiple approaches can help reveal what works, what does not, and what best aligns with the original instructional intention.
4. Learn by Experimenting
This project also reminded me that learning AI tools is often about experimentation rather than mastery from the beginning. Throughout the project, I explored 12 AI tools and created more than 20 final outputs through what was probably over 500 prompts and iterations.
I found that newer AI tools are becoming increasingly intuitive and accessible while offering more advanced capabilities. My recommendation, therefore, is simple: try things out and play around with the tools. You do not need to be tech-savvy or familiar with coding to begin. Start with small steps, experiment with prompts, evaluate the results, and revise.
Through this process, I also discovered that what might initially feel like simply “using AI” can become a form of vibe coding—using natural-language interaction with AI to create, modify, and prototype something that you might previously have thought was beyond your technical abilities. The process opened up new possibilities for me as a learning designer and made me curious about what else could be created through this emerging way of working.
5. Looking Ahead
For future work, I would like to take this project one step further by designing and developing a standalone web app for faculty and learning designers to transform syllabi or other learning content into more interactive and engaging formats.
I found several existing websites that offer similar services, but there is still room to improve how these tools address Universal Design for Learning (UDL), Web Content Accessibility Guidelines (WCAG), and search-based design and navigation. Rather than simply making course content look more visually appealing, I am interested in exploring how AI-assisted design can make learning content more purposeful, accessible, navigable, and engaging.
This could be an interesting next project—and perhaps another opportunity to continue exploring not only what AI can create, but what we intentionally choose to create with it.
Special Thanks Go To
I would like to express my sincere gratitude to my practicum partners, Faeyza and Natasha from the UBC LDDI team, for their incredible support and guidance throughout this project. Their thoughtful feedback, encouragement, and recommendations for tools and resources provided invaluable direction as I developed and refined my project. I am truly grateful for their presence and support throughout this learning journey.